The proper handling and processing of data is at the core of the Insurance business, the process of underwriting is based on data analytics. Over the last few decades, developments in computing power and predictive algorithms, have allowed these companies to build more sophisticated Data Analytics solutions. These solutions have led to improving the customer experience by better customer segmentation and targeted offers, enhancing risk assessment in underwriting, reducing the cost of claims and identifying new sources of sustainable growth. A recent survey explained that predictive analytics can reduce more than two-thirds of insurers underwriting expenses which directly support in increase of sales and profitability.
Over the last year’s many insurance providers have invested in implementation of Data Analytics based solutions. Data Analytics is key to survive in a fast changing environment, but Insurance companies are still facing multiple challenges that prevent them for reaching the potential of Data Analytics solutions:
1. Scarcity of trained manpower to work on Data Analytics enabled platform.
2. Mismatch between business sense and Data Analytics expertise.
3. Data Analytics solutions are not easily understood by working people.
4. The value of Data Analytics solutions is not defined or not measured structurally, therefore it is unclear if the investment and maintenance is justified
5. The ultimate objective of running business is profit, but new technology developments requires continuous outflow of cash due to shift and change.
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